• Journal of Korea Spatial Information System Society
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• v.3 no.1 s.5
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• pp.49-62
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• 2001

Recently, component-based software has become main trends in designing and developing computer software products. This component-based software has advantage of the interoperability on distributed computing environment and the reusability of pre-developed components. Also, GIS is designed and implemented with this component-based methodology, called Open GIS Component. OGC(OpenGIS Consortium) have announced various implementation and design specification and topic in GIS. In GIS, Spatial analysis functions like network analysis, TIN analysis are very important function and basically, estimate system functionality and performance using this analysis methods. The simple feature geometry specification is announced by OGC to increase the full interoperability of various spatial data. This specification includes just geometry spatial data model. However, in GIS which manages spatial data, not only geometric data but also topological data and various analysis functions have been used. The performance of GIS depends on how this geometric and topological data is managed well and how various spatial analyses are executed efficiently. So it requires integrated spatial data model between geometry and topology and extended data model of topology for spatial analysis, in case network analysis and TIN analysis in open GIS component. In this paper, we design analysis component like network analysis component and TIN analysis component. To manage topological information for spatial analysis in open GIS component, we design extended data model of simple feature geometry for spatial analysis. In addition to, we design the overall system architecture of open GIS component contained this topology model for spatial analysis.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.983-989
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• 2009

This study aims to systematically identify direct and indirect factors that influence labor productivity and to build a model that mathematically quantifies them so as to efficiently manage and increase labor productivity in the construction work. This study was performed based on the productivity model for workers in reinforced concrete construction projects, because it aims to establish a general construction labor productivity model that reflects many factors that influence labor productivity. Using statistical analysis, we found that the components that significantly influence productivity were the worker component, the work characteristic component, the work technique component, the work management component, the equipment & materials component, and the work guide component, while the work delay components did not significantly influence productivity. In addition, a priority analysis was performed based on the components that showed statistically significant effects. The results of the analysis indicated that the influence of work management component and the work technique component is more than that of the worker component and the work characteristic component. The construction labor productivity model that was formulated in this study could be used for the determining the standard productivity during the initial planning stage, so the best strategy for increasing labor productivity could be formulated.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.52 no.2
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• pp.53-60
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• 2003

This paper deals with steady-state analysis of a single-phase line-start permanent magnet synchronous motor. In order to analyze the steady-state characteristics, the asymmetric single-phase line-start synchronous motor is converted to the symmetric two-phase synchronous motor, that is, the asymmetric magnetic field is separated from the positive and the negative symmetric components using symmetrical-component theory. The analysis method of the synchronous motor on the d-q axis coordinates is used for the positive component and the equivalent circuit of the induction motor is applied for the negative component analysis. Moreover, d-q axis inductance considering current phase angle is applied to positive component analysis for precise characteristic analysis. In order to validate the proposed analysis method, the analysis results are compared with the experimental results.

• The Korean Journal of Applied Statistics
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• v.27 no.1
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• pp.31-41
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• 2014

Biplot is a useful graphical method to simultaneously explore the rows and columns of a two-way data matrix. In particular, principal component factor biplot is a graphical method to describe the interrelationship among many variables in terms of a few underlying but unobservable random variables called factors. If we consider the unobservable variables (which are mutually independent and also non-Gaussian), we can apply the independent component analysis decomposing a mixture of non-Gaussian in its independent components. In this case, if we apply the principal component factor analysis, we cannot clearly describe the interrelationship among many variables. Therefore, in this study, we apply the independent component analysis of Jutten and Herault (1991) decomposing a mixture of non-Gaussian in its independent components. We suggest an independent component biplot to interpret the independent component analysis graphically.

• Journal of the Korean Data and Information Science Society
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• v.14 no.3
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• pp.623-630
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• 2003

Recently, Tanaka(1988) derived two influence functions related to an eigenvalue problem $(A-\lambda_sI)\upsilon_s=0$ of real symmetric matrix A and used them for sensitivity analysis in principal component analysis. In this paper, we deal with the perturbation expansions up to quadratic terms of the same functions and discuss the application to sensitivity analysis in principal component regression analysis(PCRA). Numerical example is given to show how the approximation improves with the quadratic term.

• Journal of the Korean Society of Industry Convergence
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• v.8 no.3
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• pp.143-148
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• 2005

This paper presents a hybrid method for recognizing the faces by using principal component analysis(PCA) and fixed-point independent component analysis(FP-ICA). PCA is used to whiten the data, which reduces the effects of second-order statistics to the nonlinearities. FP-ICA is applied to extract the statistically independent features of face image. The proposed method has been applied to the problems for recognizing the 20 face images(10 persons * 2 scenes) of 324*243 pixels from Yale face database. The 3 distances such as city-block, Euclidean, negative angle are used as measures when match the probe images to the nearest gallery images. The experimental results show that the proposed method has a superior recognition performances(speed, rate). The negative angle has been relatively achieved more an accurate similarity than city-block or Euclidean.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.33 no.5
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• pp.373-380
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• 2009

The evaporation process of multi-component fuel is different from one of a single component, because the properties of each component affects among the components. In actual engine, the spatial distribution of fuel vapor concentration dominates auto-ignition and initial combustion, and depends on the volatility and diffusivity of each component fuel contained in the multi-component fuel. Then, this study proposes a simplified numerical scheme for analysis of evaporation process of multi-component fuel sprays. Evaporation process is calculated by KIVA-II code based on the simple two-phases region that is approximated by modified saturated liquid-vapor line, which was obtained by connecting the 50% distillation temperature for each component under several pressure fields. Consequently, it can be quantitatively simulated that vapor of low boiling fuel component mostly exists around nozzle and spray tip region, the high boiling duel component, on the other hand, mostly appears near the spray tip.

• Proceedings of the Korean Information Science Society Conference
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• 2002.04a
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• pp.247-249
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• 2002

본 논문에서는 주성분 분석(principal component analysis; 이하 PCA) 및 독립성분분석(independent component analysis; 이하 ICA)을 이용, 이차원 영상을 분류하여 다중해상도에서 영상간의 거리를 측정하여 PCA 와 ICA 중에서 어느 것이 영상간의 상대적 식별을 용이하게 하는지 모의 실험을 통하여 확인하고자 한다. 모의 실험 결과로부터, ICA가 PCA에 비하여 영상간의 상대적 식별이 용이하여 빨리 수렴이 되는 것을 모의 실험을 통하여 확인하였다.

• Proceedings of the Korea Contents Association Conference
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• 2003.11a
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• pp.213-217
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• 2003

In this paper, we analysize the noise robustness of MLPs(Multilayer perceptrons). Also, as a preprocessing stage of MLPs to improve noise robustness, we consider the ICA(independent component analysis) and PCA(principle component analysis). After analyzing the noise redunction effect using PCA or ICA, we verify the noise robustness of MLPs through handwritten-digit recognition simulations.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.2
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• pp.99-107
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• 2009

This paper presents an enhanced hybrid model based on Independent Component Analysis(ICA) in order to features of numeric characters in license plates. ICA which is used only in high dimensional statistical features doesn't consider statistical features in low dimension and correlation between numeric characters. To overcome the drawbacks of ICA, we propose an improved ICA with the hybrid model using both Principle Component Analysis(PCA) and Linear Discriminant Analysis(LDA). Experiment results show that the proposed model has a superior performance in feature extraction and recognition compared with ICA only as well as other hybrid models.